• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.11
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• pp.1398-1406
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• 2004

The nonlinear signals from an impedance meter for the area average void fraction in two-phase flow have been analyzed to construct a phase space trajectory. The pseudo phase space was constructed with the time delay and proper dimensions. The time delay and the embedding dimension were chosen by the average mutual information and by the false nearest neighborhood, respectively. The attractor-density-map of projected states was used to produce the two dimensional probability distribution functions (2D-PDF). Since the developed 2D-PDF showed clear distinction of the flow patterns, the flow regime identification was made with three rules and with the 2D-PDF. Also, the transition criteria of Mishima-Ishii agree well with the present results.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.108-108
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• 2004

• Proceedings of the Korean Geotechical Society Conference
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• 2003.06b
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• pp.197-226
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• 2003

터널에서의 암반분류/평가는 지보패턴결정 뿐만 아니라 터널주변암반에 대한 설계정 수 산정 및 물성평가에 있어 매우 중요한 요소라 할 수 있다. 암반분류는 각 국 또는 주요기관 별로 분류안이 만들어져 있으며, 현재 RMR분류와 Q-system이 가장 활발히 적용되고 있다. 본고에서는 터널설계단계에서 암반분류방법과 지보패턴결정과정을 고찰하였으며, 도로설계를 중심으로 적용현황을 분석하였다 또한 실제 터널시공시 암반분류 및 판정에 의한 지보공 변경사례를 살펴봄으로서 시공 중 암반분류/평가의 의미를 고찰하였다. 그리고 암반분류요소들에 대한 통계분석을 실시하여 암반분류요소들간의 상관관계를 분석하였다.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.41-47
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• 2001

In this paper, I propose a detection algorithm that can reliably separate moving objects from noisy background in the image sequence received from a camera at the fixed position. The proposed algorithm consists of four processes: generation of the difference image between the input image and the reference image. multilevel quantization of the difference image, and multistage merging in the quantized image, detection of the moving object using a back propagation in a neural network. The test results show that the proposed algorithm can detect moving objects very effectively in noisy environment.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.1
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• pp.48-53
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• 2000

The effects of the internal flow in a diesel injection nozzle on the atomization of the spray has been investigated experimentally. Flow visualization was made using a transparent acrylic model nozzle. And also, measurement of the sac chamber pressure was made for clartfying the effect of pressure fluctuation in the sac chamber on the wpray behaviors. The geometry of the model nozzle was scaled up 10 times of the actual nozzle and the injection pressure for the model nozzle was adjusted so as to achieve a Reynolds number at the discharge hole which was the same as the actual nozzle. Polystyrene tracers, a laser sheet light and a still/high speed video camera were used to visualize the flow pattern in the sac chamber. When the needle lift was small, the high turbulence in the sac chamber generated by the high velocity seat flow made the spread angle of the spray large. Cavitation which arose in the sky chamber induced the pressure fluctuation and then affects the spread angle of the spray.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.299-301
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• 2000

XML은 문서의 구조를 독립적으로 작성할 수 있어 문서의 체계적인 구조화가 가능하다. 이러한 이유로 최근, XML 문서를 구조화하여 데이터베이스에 저장, 관리하는 XML 문서 관리 시스템 연구가 활발하다. XML 문서 관리 시스템은 XML의 구조 정보를 효과적으로 표현하기 위해 여러 가지 기법을 사용하고 있다. 그러나, 기존의 방법들은 XML 문서 구성에 따라 저장 스키마가 유동적이거나 문서 정보 검색의 제약을 가지고 있을 뿐만 아니라, DTD의 문서 구조가 순환 관계와 같이 복잡한 형태를 지닐 때, 그 구조를 적절히 반영하지 못하거나, 구조를 반영하더라도 검색 시, 모든 요소를 순차적으로 탐색해야 하는 등의 문제점을 지니고 있다. 따라서 본 연구에서는 XML의 내용이나 구성에 영향받지 않는 저장 스키마를 설계하고 정보검색의 제약을 해결가능한 경로 정보를 제안한다. 또한 순환 관계를 갖는 DTD의 구조 정보를 비 순환 구조 부분과 순환 구조 부분으로 분리, 정의하고 질의처리 시, 입력되는 XML-QL을 SQL로 변환하기 위하여 XML-QL의 패턴을 분류하고 이에 따른 중간 단계의 SQL을 정의하여 질의어 변환기법을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.192-200
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• 2008

Multimodal biometrics is a method for personal authentication and verification using more than two types of biometrics data. RBF based score-level fusion uses pattern recognition algorithm for multimodal biometrics, seeking the optimal decision boundary to classify score feature vectors each of which consists of matching scores obtained from several unimodal biometrics system for each sample. In this case, all matching scores are assumed to have the same reliability. However, in recent research it is reported that the quality of input sample affects the result of biometrics. Currently the matching scores having low reliability caused by low quality of samples are not currently considered for pattern recognition modelling in multimodal biometrics. To solve this problem, in this paper, we proposed the RBF based score-level fusion approach which employs quality information of input biometrics data to adjust decision boundary. As a result the proposed method with Qualify information showed better recognition performance than both the unimodal biometrics and the usual RBF based score-level fusion without using quality information.

• Journal of the Korean Society of Hazard Mitigation
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• v.3 no.4 s.11
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• pp.119-129
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• 2003

Concrete and steel are essential structural materials in the construction. But, concrete, different from steel, consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructors. Concrete have two kinds of properties, immediately knowing properties such as slump, air contents and time dependent one like strength. Therefore, concrete mixes depend on experiences of experts. However, at point of time using High Performance Concrete, new method is wanted because of more ingredients like mineral and chemical admixtures and lack of data. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network ate used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength, slump, and air contents are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.291-291
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• 2018

하천 및 수자원의 효율적인 관리와 더불어 다양한 수공구조물의 운영 및 관리를 위해서 구조물 주변에서 발생하는 불연속 흐름 및 급변류 등의 현상과 구조물 운영을 반영한 수치해석 기법을 이용한 모델 개발의 중요성이 커지고 있다. 본 연구에서는 하천의 불연속 흐름을 모의하기 위한 1차원 흐름해석 모형(K-River)을 개발하였다. 본 모형은 천이류와 급변류를 수치적으로 안정하게 처리하기 위하여 지배방정식을 보존형 Saint-Venant 방정식으로 선정하고, FVM과 Forward Euler 방법을 이용하여 이산화를 수행하였다. 수치흐름률을 계산하기 위해서 불규칙 단면과 하상의 급경사 등에 신뢰도가 높은 기법으로 판단되는 근사 Riemann해법 중 하나인 HLL flux를 이용하였다. 개발된 K-river 모형의 검증을 위해서 해석해가 존재하는 타원형의 하상융기가 있는 하도에 적용하였으며, 국내에서 하천 설계 및 관리를 위해서 광범위하게 이용되고 있는 1차원 흐름해석 모형인 FDM기반의 HEC-RAS 모의결과와 비교 검토를 수행하였다. 그 결과, FDM기법에서는 모의되지 않는 일부 급변류 패턴을 개발 모형을 통해 모의가능하였으며, 전체적으로 K-River가 기존 모형 보다 해석해에 근사한 결과를 나타내었다. 또한, 배수문을 비롯하여 합류부, 분류부, 펌프장, 암거 등이 설치되어 운영되고 있는 아라뱃길에 적용하여 K-River의 적용성을 평가하였다. K-River를 이용하여 아라뱃길의 흐름분석을 수행한 경우가 HEC-RAS를 이용한 경우보다 수위와 유량의 유동을 시간에 따라 세밀하게 모의하였으며, 이는 배수효과에 의한 파의 전달이 FDM기법 대비 정확히 모의되기 때문으로 판단된다. 추후 연구에서는 현재보다 시간간격을 상세화 하여 수집된 관측수위를 통해 추가적인 검증을 수행하고, 다양한 특성을 가진 타 하천 등에 적용하여 모형의 적용성을 확대하고자 한다.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.697-712
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• 2020

New infectious diseases have broken out repeatedly across the world over the last 20 years; COVID-19 is causing drastic changes and damage to daily lives. Furthermore, as there is no denying that new epidemics will appear in the future, there is a continuous need to develop measures aimed towards responding to economic damage. Against this backdrop, the living population is an important indicator that shows changes in citizens' life patterns. This study analyzes time-based and socio-environmental characteristics by detecting and classifying changes in everyday life caused by COVID-19 from the perspective of the floating population. k-shape Clustering is used to classify living population data of each of the 424 dong's in Seoul measured by the hour; then by applying intervention analysis and One-way ANOVA, each cluster's characteristics and aspects of change in the living population occurring in the aftermath of COVID-19 are scrutinized. In conclusion, this study confirms each cluster's obvious characteristics in changes of population flows before and after the confirmation of coronavirus patients and distinguishes groups that reacted sensitively to the intervention times on the basis of COVID-related incidents from those that did not.